CCCL (CUDA C++ Core Libraries) provides: - CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk) - Thrust: high-level parallel algorithms (transform_reduce, sort, scan) - libcudacxx: CUDA C++ standard library (atomics, barriers, memory) - cudax: experimental features (memory resources, allocators) - Tuning policies: per-SM hardware-specific algorithm parameters Competition optimization vectors mapped to CCCL: - Output TPS (83% weight): warp_reduce, block_reduce, device_topk - Input TPS (14% weight): device_scan, block_load, prefetch - Cache TPS (3% weight): prefix caching strategy patterns - Memory (0.9 util): pooled/cached/buddy allocators Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only) License: Apache-2.0
160 lines
4.1 KiB
Plaintext
160 lines
4.1 KiB
Plaintext
//===----------------------------------------------------------------------===//
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//
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// Part of CUDA Experimental in CUDA C++ Core Libraries,
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// under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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// SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES.
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//
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//===----------------------------------------------------------------------===//
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#ifndef _CUDAX__CONTAINER_VECTOR
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#define _CUDAX__CONTAINER_VECTOR
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#include <cuda/__cccl_config>
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#if defined(_CCCL_IMPLICIT_SYSTEM_HEADER_GCC)
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# pragma GCC system_header
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#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_CLANG)
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# pragma clang system_header
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#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_MSVC)
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# pragma system_header
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#endif // no system header
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#include <thrust/device_vector.h>
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#include <thrust/host_vector.h>
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#include <cuda/__stream/stream_ref.h>
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#include <cuda/std/__type_traits/maybe_const.h>
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#include <cuda/std/span>
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#include <cuda/experimental/__detail/utility.cuh>
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#include <cuda/experimental/__launch/param_kind.cuh>
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#include <cstdio>
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namespace cuda::experimental
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{
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using ::cuda::std::span;
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using ::thrust::device_vector;
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using ::thrust::host_vector;
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template <typename _Ty>
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class vector
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{
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public:
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vector() = default;
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explicit vector(size_t __n)
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: __h_(__n)
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{}
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_Ty& operator[](size_t __i) noexcept
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{
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__dirty_ = true;
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return __h_[__i];
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}
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const _Ty& operator[](size_t __i) const noexcept
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{
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return __h_[__i];
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}
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private:
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void sync_host_to_device([[maybe_unused]] ::cuda::stream_ref __str, __detail::__param_kind __p) const
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{
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if (__dirty_)
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{
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if (__p == __detail::__param_kind::_out)
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{
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// There's no need to copy the data from host to device if the data is
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// only going to be written to. We can just allocate the device memory.
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__d_.resize(__h_.size());
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}
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else
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{
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// TODO: use a memcpy async here
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__d_ = __h_;
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}
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__dirty_ = false;
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}
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}
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void sync_device_to_host(::cuda::stream_ref __str, __detail::__param_kind __p) const
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{
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if (__p != __detail::__param_kind::_in)
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{
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// TODO: use a memcpy async here
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__str.sync(); // wait for the kernel to finish executing
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__h_ = __d_;
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}
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}
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template <__detail::__param_kind _Kind>
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class __action //: private __detail::__immovable
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{
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using __cv_vector = ::cuda::std::__maybe_const<_Kind == __detail::__param_kind::_in, vector>;
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public:
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explicit __action(::cuda::stream_ref __str, __cv_vector& __v)
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: __str_(__str)
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, __v_(__v)
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{
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__v_.sync_host_to_device(__str_, _Kind);
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}
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__action(__action&&) = delete;
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~__action()
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{
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try
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{
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__v_.sync_device_to_host(__str_, _Kind);
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}
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catch (const ::std::exception& e)
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{
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static_cast<void>(
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::fprintf(stderr, "Exception occurred during host to device synchronization: %s\n", e.what()));
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}
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catch (...)
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{
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static_cast<void>(::fprintf(stderr, "Unknown exception occurred during host to device synchronization\n"));
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}
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}
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::cuda::std::span<_Ty> transformed_argument() const
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{
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return {__v_.__d_.data().get(), __v_.__d_.size()};
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}
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private:
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::cuda::stream_ref __str_;
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__cv_vector& __v_;
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};
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[[nodiscard]] friend __action<__detail::__param_kind::_inout>
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transform_launch_argument(::cuda::stream_ref __str, vector& __v)
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{
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return __action<__detail::__param_kind::_inout>{__str, __v};
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}
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[[nodiscard]] friend __action<__detail::__param_kind::_in>
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transform_launch_argument(::cuda::stream_ref __str, const vector& __v)
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{
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return __action<__detail::__param_kind::_in>{__str, __v};
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}
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template <__detail::__param_kind _Kind>
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[[nodiscard]] friend __action<_Kind>
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transform_launch_argument(::cuda::stream_ref __str, __detail::__box<vector, _Kind> __b)
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{
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return __action<_Kind>{__str, __b.__val};
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}
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mutable host_vector<_Ty> __h_;
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mutable device_vector<_Ty> __d_{};
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mutable bool __dirty_ = true;
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};
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} // namespace cuda::experimental
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#endif
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